General maximum likelihood empirical Bayes estimation of normal means

DOI10.1214/08-AOS638zbMath1168.62005arXiv0908.1709OpenAlexW2129297925WikidataQ107392506 ScholiaQ107392506MaRDI QIDQ2388976

Wenhua Jiang, Cun-Hui Zhang

Publication date: 22 July 2009

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0908.1709

zbMATH Keywords

empirical Bayes white noise shrinkage estimator adaptive estimation threshold estimator compound estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Empirical decision procedures; empirical Bayes procedures (62C12)

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Cites Work